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We investigate the generalization boundaries of current Multimodal Large Language Models (MLLMs) via comprehensive evaluation under out-of-distribution scenarios and domain-specific tasks.
Martín Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz · 1907
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Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz · 1907
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Deep domain-adversarial image generation for domain generalisation
Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, and Tao Xiang · 2003
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Learning to generate novel domains for domain generalization
Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, and Tao Xiang · 2007
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The mnist database of handwritten digit images for machine learning research [best of the web]
Li Deng · 2012
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Unbiased metric learning: On the utilization of multiple datasets and web images for softening bias
Chen Fang, Ye Xu, and Daniel N Rockmore · 2013
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Muhammad Ghifary, W Bastiaan Kleijn, Mengjie Zhang, and David Balduzzi · 2015
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Deeper, broader and artier domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales · 2017
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Nih clinical center provides one of the largest publicly available chest x-ray datasets to scientific community, 2017
National Institutes of Health et al · 2017
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Deep hashing network for unsupervised domain adaptation
Hemanth Venkateswara, Jose Eusebio, Shayok Chakraborty, and Sethuraman Panchanathan · 2017
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Recognition in terra incognita
Sara Beery, Grant Van Horn, and Pietro Perona · 2018
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Functional map of the world
Gordon Christie, Neil Fendley, James Wilson, and Ryan Mukherjee · 2018
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Best sources forward: Domain generalization through source-specific nets
Massimiliano Mancini, Samuel Rota Bulò, Barbara Caputo, and Elisa Ricci · 2018
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The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions
Philipp Tschandl, Cliff Rosendahl, and Harald Kittler · 2018
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Regularized learning for domain adaptation under label shifts
Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, and Animashree Anandkumar · 2019
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Domain generalization by solving jigsaw puzzles
Fabio Maria Carlucci, Antonio D’Innocente, Silvia Bucci, Barbara Caputo, and Tatiana Tommasi · 2019
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Domain generalization via model-agnostic learning of semantic features
Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, and Ben Glocker · 2019
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Domain generalization via multidomain discriminant analysis, 2019
Shoubo Hu, Kun Zhang, Zhitang Chen, and Laiwan Chan · 2019
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Episodic training for domain generalization
Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, and Timothy M. Hospedales · 2019
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Chembl: towards direct deposition of bioassay data
David Mendez, Anna Gaulton, A Patrícia Bento, Jon Chambers, Marleen De Veij, Eloy Félix, María Paula Magariños, Juan F Mosquera, Prudence Mutowo, Michał Nowotka, et al · 2019
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Moment matching for multi-source domain adaptation
Xingchao Peng, Qinxun Bai, Xide Xia, Zijun Huang, Kate Saenko, and Bo Wang · 2019
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Learning to optimize domain specific normalization for domain generalization
Seonguk Seo, Yumin Suh, Dongwan Kim, Jongwoo Han, and Bohyung Han · 2019
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Language models are few-shot learners, 2020
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, and et al · 2020
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Sviro: Synthetic vehicle interior rear seat occupancy dataset and benchmark
Steve Dias Da Cruz, Oliver Wasenmuller, Hans-Peter Beise, Thomas Stifter, and Didier Stricker · 2020
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Sharpness-aware minimization for efficiently improving generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, and Behnam Neyshabur · 2020
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In search of lost domain generalization
Ishaan Gulrajani and David Lopez-Paz · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, and et al · 2020
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Efficient domain generalization via common-specific low-rank decomposition
Vihari Piratla, Praneeth Netrapalli, and Sunita Sarawagi · 2020
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Learning to learn single domain generalization
Fengchun Qiao, Long Zhao, and Xi Peng · 2020
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Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, Rebecca Roelofs, Raphael Gontijo-Lopes, and et al · 2022
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Towards principled disentanglement for domain generalization
Hanlin Zhang, Yi-Fan Zhang, Weiyang Liu, Adrian Weller, Bernhard Scholkopf, and Eric P. Xing · 2022
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Opt: Open pre-trained transformer language models, 2022
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, and et al · 2022
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A closer look at in-context learning under distribution shifts, 2023
Kartik Ahuja and David Lopez-Paz · 2023
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Openflamingo: An open-source framework for training large autoregressive vision-language models, 2023
Anas Awadalla, Irena Gao, Josh Gardner, Jack Hessel, Yusuf Hanafy, and et al · 2023
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Devansh Arpit, Huan Wang, Yingbo Zhou, and Caiming Xiong · 2021
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The iwildcam 2021 competition dataset
Sara Beery, Arushi Agarwal, Elijah Cole, and Vighnesh Birodkar · 2021
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Swad: Domain generalization by seeking flat minima
Junbum Cha, Sanghyuk Chun, Kyungjae Lee, Han-Cheol Cho, Seunghyun Park, and et al · 2021
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, and et al · 2021
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Semi-supervised screening of covid-19 from positive and unlabeled data with constraint non-negative risk estimator
Zhongyi Han, Rundong He, Tianyang Li, Benzheng Wei, Jian Wang, and Yilong Yin · 2021
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Wilds: A benchmark of in-the-wild distribution shifts, 2021
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, and et al · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Reproducible scaling laws for contrastive language-image learning
Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, and Jenia Jitsev · 2023
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Promptstyler: Prompt-driven style generation for source-free domain generalization
Junhyeong Cho, Gilhyun Nam, Sungyeon Kim, Hunmin Yang, and Suha Kwak · 2023
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Instructblip: Towards general-purpose vision-language models with instruction tuning. arxiv 2023
W Dai, J Li, D Li, AMH Tiong, J Zhao, and et al · 2023
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Palm-e: An embodied multimodal language model, 2023
Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, and et al · 2023
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Ct-xcov: a ct-scan based explainable framework for covid-19 diagnosis
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Mme: A comprehensive evaluation benchmark for multimodal large language models
Chaoyou Fu, Peixian Chen, Yunhang Shen, Yulei Qin, Mengdan Zhang, Xu Lin, Jinrui Yang, Xiawu Zheng, Ke Li, Xing Sun, et al · 2023
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Llama-adapter v2: Parameter-efficient visual instruction model
Peng Gao, Jiaming Han, Renrui Zhang, Ziyi Lin, Shijie Geng, Aojun Zhou, Wei Zhang, Pan Lu, Conghui He, Xiangyu Yue, et al · 2023
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How well does gpt-4v (ision) adapt to distribution shifts? a preliminary investigation
Zhongyi Han, Guanglin Zhou, Rundong He, Jindong Wang, Xing Xie, Tailin Wu, Yilong Yin, Salman Khan, Lina Yao, Tongliang Liu, et al · 2023
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Mathvista: Evaluating math reasoning in visual contexts with gpt-4v, bard, and other large multimodal models
Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, and Jianfeng Gao · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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Model ratatouille: Recycling diverse models for out-of-distribution generalization
Alexandre Ramé, Kartik Ahuja, Jianyu Zhang, Matthieu Cord, Léon Bottou, and David Lopez-Paz · 2023
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Generative multimodal models are in-context learners
Quan Sun, Yufeng Cui, Xiaosong Zhang, Fan Zhang, Qiying Yu, Zhengxiong Luo, Yueze Wang, Yongming Rao, Jingjing Liu, Tiejun Huang, et al · 2023
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Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, and et al · 2023
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Llama: Open and efficient foundation language models, 2023
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, and et al · 2023
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The dawn of lmms: Preliminary explorations with gpt-4v (ision)
Zhengyuan Yang, Linjie Li, Kevin Lin, Jianfeng Wang, Chung-Ching Lin, and et al · 2023
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mplug-owl: Modularization empowers large language models with multimodality
Qinghao Ye, Haiyang Xu, Guohai Xu, Jiabo Ye, Ming Yan, Yiyang Zhou, Junyang Wang, Anwen Hu, Pengcheng Shi, Yaya Shi, et al · 2023
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Revisiting out-of-distribution robustness in nlp: Benchmark, analysis, and llms evaluations
Lifan Yuan, Yangyi Chen, Ganqu Cui, Hongcheng Gao, Fangyuan Zou, Xingyi Cheng, Heng Ji, Zhiyuan Liu, and Maosong Sun · 2023
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General-purpose in-context learning by meta-learning transformers, 2024
Louis Kirsch, James Harrison, Jascha Sohl-Dickstein, and Luke Metz · 2024
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Robust place categorization with deep domain generalization
Massimiliano Mancini, Samuel Rota Bulò, Barbara Caputo, and Elisa Ricci · 2093
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